Using workload profiling and analytics to understand and score complexity of test environments and workloads

ABSTRACT

Aspects of the present invention include a method, system and computer program product determining, scoring and reporting the complexity of customer and test environments and workloads. The method includes a processor performing an accounting of factors related to complexity of a plurality of environments and workloads; determining one or more formulas to use for determining an overall score and ranking for each one of the plurality of environments and workloads; collecting relative environment and workload data; determining a complexity score for each one of the plurality of environments and workloads; and determining a complexity ranking for each one of the plurality of environments and workloads.

BACKGROUND

The present invention relates to the testing of software, hardware,firmware, and/or other disciplines, and more specifically, to a method,system and computer program product that implement aspects of workloadand operational profiling, coupled with business analytics, therebyresulting in improvements in the testing of customer software.

In the field of software testing, as in many other technical fields,improvements are constantly being sought, primarily for cost andaccuracy reasons. A fundamental goal of software testing, in theory, isto identify all of the problems in a customer's software program beforethe program is released for use by the customer. However, in reality,this is far from the case as typically a software program is released tothe customer having some number of problems that were unidentifiedduring the software development and testing process.

A relatively more proactive approach to improving software testing issought that employs traditional methods of understanding characteristicsof clients' environments, augmented with a process of data miningempirical systems data. Such client environment and workload profilinganalysis may result in software test improvements based oncharacteristics comparisons between the client and the testenvironments.

SUMMARY

According to one or more embodiments of the present invention, acomputer-implemented method includes performing, by a processor, anaccounting of factors related to complexity of a plurality ofenvironments and workloads; determining, by the processor, one or moreformulas to use for determining an overall score and ranking for eachone of the plurality of environments and workloads; collecting, by theprocessor, relative environment and workload data; determining, by theprocessor, a complexity score for each one of the plurality ofenvironments and workloads; and determining, by the processor, acomplexity ranking for each one of the plurality of environments andworkloads.

According to another embodiment of the present invention, a systemincludes a processor in communication with one or more types of memory,the processor configured to perform an accounting of factors related tocomplexity of a plurality of environments and workloads; to determineone or more formulas to use for determining an overall score and rankingfor each one of the plurality of environments and workloads; to collectrelative environment and workload data; to determine a complexity scorefor each one of the plurality of environments and workloads; and todetermine a complexity ranking for each one of the plurality ofenvironments and workloads.

According to yet another embodiment of the present invention, a computerprogram product includes a non-transitory storage medium readable by aprocessing circuit and storing instructions for execution by theprocessing circuit for performing a method that includes performing anaccounting of factors related to complexity of a plurality ofenvironments and workloads; determining one or more formulas to use fordetermining an overall score and ranking for each one of the pluralityof environments and workloads; collecting relative environment andworkload data; determining a complexity score for each one of theplurality of environments and workloads; and determining a complexityranking for each one of the plurality of environments and workloads.

Additional features and advantages are realized through the techniquesof the present invention. Other embodiments and aspects of the inventionare described in detail herein and are considered a part of the claimedinvention. For a better understanding of the invention with theadvantages and the features, refer to the description and to thedrawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The subject matter which is regarded as the invention is particularlypointed out and distinctly claimed in the claims at the conclusion ofthe specification. The forgoing and other features, and advantages ofthe invention are apparent from the following detailed description takenin conjunction with the accompanying drawings in which:

FIG. 1 depicts a cloud computing environment according to one or moreembodiments of the present invention;

FIG. 2 depicts abstraction model layers according to one or moreembodiments of the present invention;

FIG. 3 is a block diagram illustrating one example of a processingsystem for practice of the teachings herein;

FIG. 4 is a flow diagram of a method for determining, scoring andreporting the complexity of customer and test environments and workloadsin accordance with one or more embodiments of the present invention.

DETAILED DESCRIPTION

It is understood in advance that although this disclosure includes adetailed description on cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 1, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 comprises one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 1 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 2, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 1) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 2 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and a method 96 for determining, scoring andreporting the complexity of customer and test environments and workloadsin accordance with one or more embodiments of the present invention.

Referring to FIG. 3, there is shown a processing system 100 forimplementing the teachings herein according to one or more embodiments.The system 100 has one or more central processing units (processors) 101a, 101 b, 101 c, etc. (collectively or generically referred to asprocessor(s) 101). In one embodiment, each processor 101 may include areduced instruction set computer (RISC) microprocessor. Processors 101are coupled to system memory 114 and various other components via asystem bus 113. Read only memory (ROM) 102 is coupled to the system bus113 and may include a basic input/output system (BIOS), which controlscertain basic functions of system 100.

FIG. 3 further depicts an input/output (I/O) adapter 107 and a networkadapter 106 coupled to the system bus 113. I/O adapter 107 may be asmall computer system interface (SCSI) adapter that communicates with ahard disk 103 and/or tape storage drive 105 or any other similarcomponent. I/O adapter 107, hard disk 103, and tape storage device 105are collectively referred to herein as mass storage 104. Operatingsystem 120 for execution on the processing system 100 may be stored inmass storage 104. A network adapter 106 interconnects bus 113 with anoutside network 116 enabling data processing system 100 to communicatewith other such systems. A screen (e.g., a display monitor) 115 isconnected to system bus 113 by display adaptor 112, which may include agraphics adapter to improve the performance of graphics intensiveapplications and a video controller. In one embodiment, adapters 107,106, and 112 may be connected to one or more I/O busses that areconnected to system bus 113 via an intermediate bus bridge (not shown).Suitable I/O buses for connecting peripheral devices such as hard diskcontrollers, network adapters, and graphics adapters typically includecommon protocols, such as the Peripheral Component Interconnect (PCI).Additional input/output devices are shown as connected to system bus 113via user interface adapter 108 and display adapter 112. A keyboard 109,mouse 110, and speaker 111 all interconnected to bus 113 via userinterface adapter 108, which may include, for example, a Super I/O chipintegrating multiple device adapters into a single integrated circuit.

In exemplary embodiments, the processing system 100 includes a graphicsprocessing unit 130. Graphics processing unit 130 is a specializedelectronic circuit designed to manipulate and alter memory to acceleratethe creation of images in a frame buffer intended for output to adisplay. In general, graphics processing unit 130 is very efficient atmanipulating computer graphics and image processing, and has a highlyparallel structure that makes it more effective than general-purposeCPUs for algorithms where processing of large blocks of data is done inparallel.

Thus, as configured in FIG. 3, the system 100 includes processingcapability in the form of processors 101, storage capability includingsystem memory 114 and mass storage 104, input means such as keyboard 109and mouse 110, and output capability including speaker 111 and display115. In one embodiment, a portion of system memory 114 and mass storage104 collectively store an operating system to coordinate the functionsof the various components shown in FIG. 3.

In accordance with one or more embodiments of the present invention,methods, systems, and computer program products are disclosed fordetermining, scoring and reporting the complexity of customer and testenvironments and workloads.

In one or more embodiments of the present invention, the method 200 maybe embodied in software that is executed by computer elements locatedwithin a network that may reside in the cloud, such as the cloudcomputing environment 50 described hereinabove and illustrated in FIGS.1 and 2. In other embodiments, the computer elements may reside on acomputer system or processing system, such as the processing system 100described hereinabove and illustrated in FIG. 3, or in some other typeof computing or processing environment.

After a start operation in block 204, an operation in block 208 takes orperforms an accounting of a number of various environment and workloadcomplexity factors and characteristics, individually and/or collectivelyin various groupings, to determine or calculate various metricsincluding component level and an overall complexity score or grade andrankings (e.g., each workload's complexity scores, by applicablesub-area and overall score). The determined or calculated metrics may bestored in a database.

These environment and workload complexity factors and characteristicsmay include, for example and without limitation, environmentconfigurations, including: server; storage; network; Sysplex, LPAR,Adapter, etc.; HMC; other IBM hardware platforms/products; dedicated vs.shared resources; physical vs. virtual resources; z/OS, zVM, zLinux,etc.; middleware including CICS, DB2, IMS, MQ, WAS, and others; otherIBM software platforms/products; Cloud (Compute, Storage, Network); andOEM hardware and software platforms and products. They may also include:functional coverage; scalability reliability; availability;serviceability; error recoverability; upgrades and migrations;performance indicators including response times, transaction rates,etc.; products; product combinations, interaction, dependencies; crossplatform product combinations, interactions and dependencies; systems;problem discovery/defect identification; PMR generation and severities;APAR generation and severities; skills requirements; additionalstructured and unstructured workload internals information as providedby customer subject matter expert(s); and additional structured andunstructured workload internals information as provided by IBM Design,Development, Performance, Support, and/or Test Subject Matter Expert(s).

In an operation in block 212, the necessary formulas are determined toproperly score and rank these complexity characteristics andrequirements. This may be done through consultation with subject matterexperts from each environment and workload to be analyzed for complexityimplementation, scoring and ranking. The subject matter experts mayprovide information, recommendations and/or guidelines. The formulas maybe stored in a database as a preparation or prerequisite for analyticsprocessing.

In an operation in block 216, acquire or collect the relativeenvironment and workload data using the current and continuallyexpanding customer profiling and analytics discipline techniques fordata collection and curation. These techniques include, for example andwithout limitation, environment and workload and operationalquestionnaires, interviews, workshops, deep dives, problem historyanalysis, social and traditional media analysis, empirical dataanalysis, and more. This environment and workload data may be stored ina database as a preparation or prerequisite for analytics processing.

In an operation in block 220, the complexity scores for each environmentand workload to be analyzed are determined or calculated using, forexample, the formulas determined in the operation in block 212. Thesecomplexity scores may be stored in a database.

An operation in block 224 determines or calculates the complexityranking of each environment and workload to be analyzed in relation tovarious previously collected customer and/or test environment andworkload data and through a variety of customer and/or test groupings.These customer and/or test groupings can include a variety ofclassifications, including by geography, country, culture, industry,etc. as well as the overall global customer and/or test set. Thesecomplexity rankings may be stored in a database.

Next, a decision operation in block 228 determines whether or not tovisualize the complexity factors and implementation of this iteration ofthe method 200. If so, in an operation in block 232, the complexityenvironment and workload factors and characteristics (includingimplementation, data/observations, formulas, scores, rankings, and otherrelative information) are visually presented in a highly intuitive,customizable, negotiable, descriptive, and flexible dashboard typeinterface and/or through other desired visualizations.

Next, a decision operation in block 236 determines whether or not togenerate report(s) for the complexity factors and characteristics ofthis iteration of the method 200. If not, the method 200 branches backto the operation in block 208. If so, in an operation in block 240, thecomplexity environment and workload factors and characteristics(including implementation, data/observations, formulas, scores,rankings, and other relative information) are presented in a highlyintuitive, customizable, negotiable, descriptive, and flexible cannedand/or end user designed and generated report(s). Then store thesecomplexity factors report specifications and data in a database, foramong other purposes, for current/future statistical analyses and forcurrent/future time series observations and analyses. The method 200then branches back to the operation in block 208 in which the methoditerates the customer profiling and analytics of complexity factors andcharacteristics as changes are made to the environment and/or workload.

Given that Test workload runs have different levels of complexity, andcan be resource and time intensive, limited in availability, andfinancially expensive to configure, stage, run, and analyze, and canspan multiple days or even weeks (including non-user monitored off-shiftand weekend time), providing a run time and historical way to assess andscore customer and test workload complexity can be potentiallyrelatively cost effective.

According to embodiments of the present invention, the run time andhistorical workload complexity report scoring provides multiplecapabilities, efficiencies, and financial benefits for the test user oroperator and/or customer including: to understand the run timecomplexity of the customer workload (software, hardware, firmware) andwhat corrective test workload run time adjustments may be required toachieve (if possible); to tune test workloads much closer to theirtarget complexity goal(s) through the very nature of faster, run timenotification and awareness, as well as insightful, analytics drivenhistorical reference; to significantly reduce the amount of limited andhigh value System z systems, storage, network, environmental, personneltime and resources to accomplish test objectives, resulting in bothfinancial savings and reduced environmental impact; to increase testplan efficiency through expanded test coverage, resulting in enhancedproduct quality and greater customer satisfaction. By the reduction ofrepeat test workload runs through higher individual workload runcomplexity effectiveness, the test user/operator can run additionaland/or expanded test cases/scenarios, and ensure each workload runmaximizes a successful outcome; and to provide insights to the customeron potential workload complexity reductions and/or efficiencies (i.e.,possibly determine ways to simplify the customer workload should therebe opportunities to do so). These potential customer workload complexityreductions/efficiencies could result in a wide range of customerbenefits including financial and skills savings, reducedproblems/outages, faster problem determination and resolution, enhancedperformance, and more.

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions execute entirely on the user's computer,partly on the user's computer, as a stand-alone software package, partlyon the user's computer and partly on a remote computer or entirely onthe remote computer or server. In the latter scenario, the remotecomputer may be connected to the user's computer through any type ofnetwork, including a local area network (LAN) or a wide area network(WAN), or the connection may be made to an external computer (forexample, through the Internet using an Internet Service Provider). Insome embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The following definitions and abbreviations are to be used for theinterpretation of the claims and the specification. As used herein, theterms “comprises,” “comprising,” “includes,” “including,” “has,”“having,” “contains” or “containing,” or any other variation thereof,are intended to cover a non-exclusive inclusion. For example, acomposition, a mixture, process, method, article, or apparatus thatcomprises a list of elements is not necessarily limited to only thoseelements but can include other elements not expressly listed or inherentto such composition, mixture, process, method, article, or apparatus.

As used herein, the articles “a” and “an” preceding an element orcomponent are intended to be nonrestrictive regarding the number ofinstances (i.e., occurrences) of the element or component. Therefore,“a” or “an” should be read to include one or at least one, and thesingular word form of the element or component also includes the pluralunless the number is obviously meant to be singular.

As used herein, the terms “invention” or “present invention” arenon-limiting terms and not intended to refer to any single aspect of theparticular invention but encompass all possible aspects as described inthe specification and the claims.

As used herein, the term “about” modifying the quantity of aningredient, component, or reactant of the invention employed refers tovariation in the numerical quantity that can occur, for example, throughtypical measuring and liquid handling procedures used for makingconcentrates or solutions. Furthermore, variation can occur frominadvertent error in measuring procedures, differences in themanufacture, source, or purity of the ingredients employed to make thecompositions or carry out the methods, and the like. In one aspect, theterm “about” means within 10% of the reported numerical value. Inanother aspect, the term “about” means within 5% of the reportednumerical value. Yet, in another aspect, the term “about” means within10, 9, 8, 7, 6, 5, 4, 3, 2, or 1% of the reported numerical value.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

1.-7. (canceled)
 8. A system comprising: a processor in communicationwith one or more types of memory, the processor configured to: performan accounting of factors related to complexity of a plurality ofenvironments and workloads; determine one or more formulas to use fordetermining an overall score and ranking for each one of the pluralityof environments and workloads; collect relative environment and workloaddata; determine a complexity score for each one of the plurality ofenvironments and workloads; and determine a complexity ranking for eachone of the plurality of environment and workloads.
 9. The system ofclaim 8 the processor further configured to determine to present invisual format the complexity score and the complexity ranking.
 10. Thesystem of claim 8 the processor further configured to determine topresent in report format the complexity score and the complexityranking.
 11. The system of claim 8 wherein the processor configured toperform an accounting of factors related to complexity of a plurality ofenvironments and workloads comprises the processor configured to performan accounting of factors related to complexity of a plurality ofenvironments and workloads individually and/or collectively in variousgroupings.
 12. The system of claim 8 wherein the factors related tocomplexity of a plurality of environments and workloads compriseenvironment configurations.
 13. The system of claim 8 wherein theprocessor configured to collect relative environment and workload datacomprises techniques including environment and workload and operationalquestionnaires, interviews, workshops, deep dives, problem historyanalysis, social and traditional media analysis, empirical dataanalysis.
 14. The system of claim 8 wherein the processor configured todetermine a complexity ranking for each one of the plurality ofenvironment and workloads comprises the processor configured todetermine a complexity ranking of each environment and workload to beanalyzed in relation to various previously collected customer and/ortest environment and workload data and through a variety of customerand/or test groupings including a variety of classifications, includingby geography, country, culture, industry, an overall global customer setand a test set.
 15. A computer program product comprising: anon-transitory storage medium readable by a processing circuit andstoring instructions for execution by the processing circuit forperforming a method comprising: performing an accounting of factorsrelated to complexity of a plurality of environments and workloads;determining one or more formulas to use for determining an overall scoreand ranking for each one of the plurality of environments and workloads;collecting relative environment and workload data; determining acomplexity score for each one of the plurality of environments andworkloads; and determining a complexity ranking for each one of theplurality of environments and workloads.
 16. The computer programproduct of claim 15 further comprising determining to present in visualformat the complexity score and the complexity ranking.
 17. The computerprogram product of claim 15 further comprising determining to present inreport format the complexity score and the complexity ranking.
 18. Thecomputer program product of claim 15 wherein performing an accounting offactors related to complexity of a plurality of environments andworkload s comprises performing an accounting of factors related tocomplexity of a plurality of environments and workloads individuallyand/or collectively in various groupings.
 19. The computer programproduct of claim 15 wherein the factors related to complexity of aplurality of environments and workloads comprise environmentconfigurations.
 20. The computer program product of claim 15 whereincollecting relative environment and workload data comprises techniquesincluding environment and workload and operational questionnaires,interviews, workshops, deep dives, problem history analysis, social andtraditional media analysis, empirical data analysis.